Botulinum toxin and platelet rich plasma as innovative therapeutic modalities for keloids
Bibliographic record
Abstract
Keloids characterize a definitely challenging type of cutaneous scars for which a diversity of therapeutic modalities has been suggested. The aim of this work was to compare the therapeutic efficacy of intralesional injection of botulinum toxin type-A (BTX-A), platelet rich plasma (PRP), and triamcinolone acetonide (TAC) in keloids. A total of 60 keloids patients were enrolled and divided randomly into three equal groups. Group I treated by intralesional BTX-A injection, group II treated by intralesional PRP injection, and group III treated by intralesional TAC injection. Clinical assessment was done by Vancouver Scar Scale (VSS), Verbal Rating Scale (VRS), and dermoscopic examination. Additionally, histopathology and immunohistochemistry of connective tissue growth factor (CTGF) expression were evaluated. The results of this study revealed significant improvement of both VSS and VRS in response to all treatment modalities. There was significant improvement of VSS in BTX-A and PRP groups more than TAC group. However, no significant difference observed between BTX-A and PRP groups. Immunohistochemical examination showed significant decrease of CTGF expression after treatment in BTX-A and PRP groups more than TAC group. In conclusion, both BTX-A and PRP could yield a chance for cosmetically better outcomes in keloids treatment than conventional TAC injection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".